实例表明遗传退火算法的高效性。
The application example shows the high effective of the algorithm.
对同一组数据的求解，第三种遗传退火算法优化效率更高。
To solve the same group data, the third method (Genetic-Simulated Annealing) is more efficiency.
并对参数进行遗传退火算法优化，使系统具有最佳结构和参数。
The simulation results show that the GFSNN is superior in modeling stochastic chaotic systems and have advantage of good precision.
可以充分利用混合遗传退火算法优异的全局最优搜索能力来寻找具有最大并行率的并行任务序列。
The hybrid GASA can be used to find the parallel test tasks arrange of the maxim parallel efficiency, for it has an excellent ability in searching for the globally optimal solution.
将遗传退火算法用于电力变压器优化设计问题的研究，介绍了算法实现过程中各种参数的选择方法并给出了具体算例。
This paper USES the method in the study of power transformer optimum design. The method to select the control parameters of the algorithm is introduced in detail.
然后，为了加快遗传算法的收敛速度减少算法执行时间引入模拟退火机制对上述算法进行优化。
Then the mechanism of Simulated Annealing is import in the algorithm above to decrease the execution time and quickens the velocity of convergence.
利用遗传模拟退火算法结合瑞典圆弧法，寻找最危险边坡进行稳定分析。
The paper tries to find the stability analysis method of dangerousest slope with heredity simulation annealing algorithm and Swedish slipcircle method.
提出了一种应用于软件测试中的基于模拟退火遗传算法的测试数据自动生成算法。
A kind of software test data automated generation method based on simulated annealing genetic algorithms is proposed.
为了提高分割速度，给出了一种改进遗传模拟退火算法。
In order to increase the speed of segmentation, an improved genetic simulated annealing is given.
为此，建立了优化消毒数学模型，并采用遗传—模拟退火混合算法对其进行求解。
Therefore, the mathematic model for optimization disinfection was set up, and the hybrid genetic-simulated annealing algorithm was used for solution.
简要地介绍了模拟退火算法，遗传算法，人工神经网络和图论算法在蛋白质结构预测中的应用。
The paper briefly introduces some modern optimum algorithms of simulated annealing, genetic algorithms, neural networks and graphic algorithms in and applied in prediction of protein structure.
使用遗传模拟退火算法来实现含水层参数反演的函数优化问题。
The genetic-simulated annealing algorithm is applied to resolving the functional optimization problems of identifying the aquifer parameters.
利用遗传模拟退火算法结合瑞典圆弧法，寻找最危险滑裂面进行边坡稳定分析。
A methodology of most dangerous sliding surface search and slope stability analysis is proposed by combining mixed genetic-simulated annealing algorithms with Sweden arc method.
利用遗传模拟退火算法结合瑞典圆弧法，寻找最危险滑裂面进行边坡稳定分析。
A methodology of most dangerous sliding surface search and slope stability analysis is proposed by combining mixed genetic-simulated annealing algorithms with Sweden arc method.
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